Simon Vogt

Neuromodulation of STDP through short-term changes in firing causality

Spike timing dependent plasticity (STDP) likely plays an important role in forming and changing connectivity patterns between neurons in our brain. In a unidirectional synaptic connection between two neurons, it uses the causal relation between spiking activity of a presynaptic input neuron and a postsynaptic output neuron to change the strength of this connection. While the nature of STDP benefits unsupervised learning of correlated inputs, any incorporation of value into the learning process needs some form of reinforcement. Chemical neuromodulators such as Dopamine or Acetylcholine are thought to signal changes between external reward and internal expectation to many brain regions, including the basal ganglia. This effect is often modelled through a direct inclusion of the level of Dopamine as a third factor into the STDP rule. While this gives the benefit of direct control over synaptic modification, it does not account for observed instantaneous effects in neuronal activity on application of Dopamine agonists. Specifically, an instant facilitation of neuronal excitability in the striatum can not be explained by the only indirect effect that dopamine-modulated STDP has on a neuron’s firing pattern. We therefore propose a model for synaptic transmission where the level of neuromodulator does not directly influence synaptic plasticity, but instead alters the relative firing causality between pre- and postsynaptic neurons. Through the direct effect on postsynaptic activity, our rule allows indirect modulation of the learning outcome even with unmodulated, two-factor STDP. However, it also does not prohibit joint operation together with three-factor STDP rules.

Computer- and robot-assisted stereotaxy for high-precision small animal brain exploration Computer- und robotergestutzte Stereotaxie fur hochprazise Exploration des Kleintierhirns

Abstract This contribution introduces a computer- and robot-assisted framework for stereotactic neurosurgery on small animals. Two major elements of this framework are presented in detail: a robotic stereotactic assistant and the software framework for placement of probes into the brain. The latter integrates modules for registration, insertion control, and preoperative path planning. Two options for path planning are addressed: (a) atlas-based planning and (b) image-based planning based on computed tomography data. The framework is tested performing robot-assisted insertion of microelectrodes and acquisition of electrophysiological recordings in vivo. Concepts for data analysis pointing towards a mapping of position and neural structure to functional data are introduced. Results show that the presented framework allows precise small animal stereotaxy and therefore offers new options for brain research. Zusammenfassung Dieser Beitrag stellt eine computer- und robotergestützte Umgebung für stereotaktische Eingriffe am Kleintier vor. Zwei Bestandteile der Umgebung werden im Detail vorgestellt: ein robotischer Assistent und die Softwareumgebung, um Instrumente im Kleintierhirn einzubringen. Letztere integriert dabei Module zur Registrierung, Steuerung des stereotaktischen Assistenten und zur Planung des Eingriffs. Zwei Optionen für die Planung werden vorgestellt: (a) atlasbasierte und (b) bildbasierte Planung auf Basis von Computertomographiedaten. Die Umgebung wird anhand der Einbringung von Mikroelektroden und der Akquise von elektrophysiologischen Ableitungen in vivo getestet. Konzepte zur Evaluierung der Daten im Hinblick auf eine Zuordnung einer räumlichen Position und einer neuronalen Struktur zu funktionellen Daten werden vorgestellt. Die Ergebnisse zeigen, dass die vorgestellte Umgebung präzise stereotaktische Eingriffe am Kleintier und neue Optionen in der Hirnforschung ermöglicht.

A unifying perspective on neuromodulatory effects on signal transmission and plasticity in D1-dominant MSN neurons

How could phasic variations in dopamine level affect the learning outcome of a spiking neural network? How may neuromodulation affect the networks instantaneous response to simultaneously arriving glutamatergic inputs? How may this depend on the brain regions involved? In our spiking phenomenological model for signal transmission across the synapse and along the dendritic tree, we propose a new approach for the influence of dopamine-like neuromodulators on the ascribed aspects, which unifies diverging views on its role in (reinforcement) learning and (attentional) contrast. We call into question the common practice of simulating dopaminergic influence on an STDP rule as a third factor, and instead show how an instantaneous effect of a dopamine-like neuromodulator on postsynaptic activity can also lead to reinforced learning outcomes. As the phasic change of neuromodulator needs to be present during glutamatergic transmission in our model, we do not account for delayed reward as stated in the distal reward problem. Instead, we assume an involvement of hippocampus and cortical working memory for long delays of reward. However, as our transmission-based model does not interfere with the standard two-factor STDP rule, it may be freely combined with existing extensions to STDP if needed.

Learning mechanisms for DA-modulated spiking networks in the basal ganglia

How the basal ganglia act to gate cortically planned actions is a topic of current discussion. Interesting work by Gurney et al [1-3] suggests an interaction between the STN and GPe as a central element of inhibition for action gating, with pathological oscillations occurring if striatal input changes due to dopamine depletion in Parkinsons disease. But what exactly changes in the signals that the striatum projects to the rest of the basal ganglia? How could the altered dopamine signal and its effect on striatal learning influence the observed functions of the basal ganglia in Parkinsonian and in healthy patients? While rate-based learning models of the basal ganglia have been suggested [5], a spiking network that reproduces basal ganglia anatomy and autonomously learns a set of possible action sequences that can then be reinforced through dopamine feedback has yet to be demonstrated. On the way to constructing such a network, we present some effects of spike timing dependent plasticity, synaptic delay, group inhibition, noisy & localised projections and dopamine modulation on feed-forward and associative spiking networks within the basal ganglia and cortex.

Computational modeling of Basal Ganglia: towards a mechanism of high frequency stimulation

Deep Brain Stimulation(DBS) with 130Hz represents an effective therapy to alleviate symptoms of some neurodegenerative diseases such as Parkinson syndrome [1]. However the mechanism underlying the observed improvement in patient’s symptoms is still under dispute. Modeling of its mechanism was first done with the Albin-Delong [2] model, which assumed two discriminated feedforward projections, from the input stage Striatum to the output stage Globus pallidus internal (GPi) and Substantia Nigra pars reticulata (SNr). However, this influential contribution neither took motor control into account nor the evidence for a selective of effect high frequency stimulation [3-5]. This study tries to model the underlying network with increasing realistic complexity and presents a spiking network model based on Izhikevich type neurons [6]. Our currently simulated model examines the firing patterns variability between GABAergic STN neuron projections depending on the firing rate. It shows features like synchronous, rythmic population spike found in experimental data of pyramidal interneuronal network [7].

Tending the source of parkinsonism through deep brain microstimulation

Introduction Descriptive models of basal ganglia operation have seen a recent increase in interest from the classical idea of direct and indirect pathways towards a more feedback-oriented view of statistic optimality [1]. These new views may prove to be valuable in explaining and finding new treatments for common basal ganglia disorders such as Parkinsons disease beyond current techniques of pure symptom fighting through widespread deep brain stimulation or chemical regulators for increasing tonic levels of dopamine.